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Analyzing male fertility data
Abstract
The new edition of this canonical text on male reproductive medicine will cement the book's market-leading position. Practitioners across many specialties - including urologists, gynecologists, reproductive endocrinologists, medical endocrinologists and many in internal medicine and family practice – will see men with suboptimal fertility and reproductive problems. The book provides an excellent source of timely, well-considered information for those training in this young and rapidly evolving field. While several recent books provide targeted 'cookbooks' for those in a male reproductive laboratory, or quick reference for practising generalists, the modern, comprehensive reference providing both a background for male reproductive medicine as well as clinical practice information based on that foundation has been lacking until now. The book has been extensively revised with a particular focus on modern molecular medicine. Appropriate therapeutic interventions are highlighted throughout.
Reproductive disorders of various severity levels can arise from the earliest stages of gamete formation: from primary germ cells to mature follicles and sperm and be provoked by internal (genetic, hormonal) and environmental (chemical and physical effects, biotoxins, etc.) factors. The study of the mechanisms and sequence of pathological changes in the course of toxicant-induced processes will make it possible to approach the regulation (prevention, compensation) of these disorders. In male gametogenesis, there is a natural mechanism for restoring disturbed reproductive properties. Thus, severe exposure of male rats to the known reprotoxicant doxorubicin leads to complete emptying of the seminal tubules and loss of fertility, but the presence of insensitive spermatogenic stem cells and Sertoli cells allows for the subsequent two to four periods of the rat spermatogenic cycle to restore the pool of seminal epithelial cells and the ability of males to fertilize.
The whole point of a diagnostic test is to use it to make a diagnosis, so we need to know the probability that the test will give the correct diagnosis. The sensitivity and specificity1 do not give us this information. Instead we must approach the data from the direction of the test results, using predictive values.
Positive predictive value is the proportion of patients with positive test results who are correctly diagnosed.
Negative predictive value is the proportion of patients with negative test results who are correctly diagnosed.
Using the same data as in the previous note,1 we know that 231 of 263 patients with abnormal liver scans had abnormal pathology, giving the proportion of correct diagnoses as 231/263 = 0.88. …
Although semen analysis is routinely used to evaluate the male partner in infertile couples, sperm measurements that discriminate between fertile and infertile men are not well defined.
We evaluated two semen specimens from each of the male partners in 765 infertile couples and 696 fertile couples at nine sites. The female partners in the infertile couples had normal results on fertility evaluation. The sperm concentration and motility were determined at the sites; semen smears were stained at the sites and shipped to a central laboratory for an assessment of morphologic features of sperm with the use of strict criteria. We used classification-and-regression-tree analysis to estimate threshold values for subfertility and fertility with respect to the sperm concentration, motility, and morphology. We also used an analysis of receiver-operating-characteristic curves to assess the relative value of these sperm measurements in discriminating between fertile and infertile men.
The subfertile ranges were a sperm concentration of less than 13.5 x 10(6) per milliliter, less than 32 percent of sperm with motility, and less than 9 percent with normal morphologic features. The fertile ranges were a concentration of more than 48.0 x 10(6) per milliliter, greater than 63 percent motility, and greater than 12 percent normal morphologic features. Values between these ranges indicated indeterminate fertility. There was extensive overlap between the fertile and the infertile men within both the subfertile and the fertile ranges for all three measurements. Although each of the sperm measurements helped to distinguish between fertile and infertile men, none was a powerful discriminator. The percentage of sperm with normal morphologic features had the greatest discriminatory power.
Threshold values for sperm concentration, motility, and morphology can be used to classify men as subfertile, of indeterminate fertility, or fertile. None of the measures, however, are diagnostic of infertility.
The late 20th century trend to delay birth of the first child until the age at which female fecundity or reproductive capacity is lower has increased the incidence of age-related infertility. The trend and its consequences have also stimulated interest in the possible factors in the female and the male that may contribute to the decline in fecundity with age; in the means that exist to predict fecundity; and in the consequences for pregnancy and childbirth. In the female, the number of oocytes decreases with age until the menopause. Oocyte quality also diminishes, due in part to increased aneuploidy because of factors such as changes in spindle integrity. Although older male age affects the likelihood of conception, abnormalities in sperm chromosomes and in some components of the semen analysis are less important than the frequency of intercourse. Age is as accurate as any other predictor of conception with assisted reproductive technology. The decline in fecundity becomes clinically relevant when women reach their mid-30s, when even assisted reproduction treatment cannot compensate for the decline in fecundity associated with delaying attempts at conceiving. Pregnancies among women aged >40 years are associated with more non-severe complications, more premature births, more congenital malformations and more interventions at birth.
Purpose: Vasovasostomy (VVS) represents the standard therapy of choice for the treatment of obstructive azoospermia following vasectomy. However, recently, intracytoplasmic sperm injection (ICSI) has been suggested by some to represent the solution for all cases of malefactor infertility regardless of its etiology based on its success rates. Therefore, we compared VVS to microsurgical epididymal sperm aspiration (MESA)/testicular extraction of sperm (TESE) and ICSI in terms of pregnancy, complications, and costs.
Microsurgical techniques in testicular sperm extraction can improve sperm retrieval in patients with nonobstructive azoospermia (NOA). However, spermatozoa retrieval rates have still been reported to be around 50% for patients with NOA. Thus, a reliable prediction method for successful outcome is needed to avoid unnecessary surgery. In this retrospective study we determined the diagnostic and predictive values of noninvasive parameters used in the treatment of patients with NOA.
We analyzed 9 preoperative factors including patient age, testicular volume and endocrinological data of 100 patients with NOA using multivariate logistic modeling. Testicular spermatozoa were retrieved successfully in 41 of the 100 patients (41%).
We found that the concentrations of follicle-stimulating hormone (FSH), total testosterone (TT) and inhibin B were considered the most influential preoperative factors. We developed a formula to calculate the probability of successful outcome, P = [1 + exp(5.201 - 0.048 x FSH - 0.449 x TT - 0.021 x inhibin B)](-1). Association of predicted probabilities and observed responses was 0.77. A predicted probability of more than 15.7% was found to be the best cutoff. Sensitivity was 71.0% and specificity was 71.4% as determined by receiver operating characteristic analysis.
We concluded that our formula should be useful for doctors considering microdissection testicular sperm extraction for patients with NOA because our equation uses noninvasive parameters without a preoperative testicular biopsy, which is a relatively invasive examination.
The clinical performance of a laboratory test can be described in terms of diagnostic accuracy, or the ability to correctly classify subjects into clinically relevant subgroups. Diagnostic accuracy refers to the quality of the information provided by the classification device and should be distinguished from the usefulness, or actual practical value, of the information. Receiver-operating characteristic (ROC) plots provide a pure index of accuracy by demonstrating the limits of a test's ability to discriminate between alternative states of health over the complete spectrum of operating conditions. Furthermore, ROC plots occupy a central or unifying position in the process of assessing and using diagnostic tools. Once the plot is generated, a user can readily go on to many other activities such as performing quantitative ROC analysis and comparisons of tests, using likelihood ratio to revise the probability of disease in individual subjects, selecting decision thresholds, using logistic-regression analysis, using discriminant-function analysis, or incorporating the tool into a clinical strategy by using decision analysis.
To evaluate cost per delivery using two different initial approaches to the treatment of postvasectomy infertility.
Model of expected costs and results in the United States in 1994.
Men with postvasectomy infertility, evaluated and treated at centers with experience in vasectomy reversal or sperm retrieval and ICSI.
Men with postvasectomy infertility, with a female partner < or = 39 years of age.
Initial microsurgical vasectomy reversal was compared with retrieved epididymal or testicular sperm. Actual treatment charges, complication rates, and pregnancy and delivery rates obtained in the United States were used for cost per delivery analysis.
Cost per delivery, delivery rates.
Cost per delivery with an initial approach of vasectomy reversal was only 19,609 to 72,521. (95% confidence interval 81,685), with an average of 71,896 for surgical epididymal sperm retrieval. The delivery rate after one cycle of sperm retrieval and ICSI was 33%.
The most cost-effective approach to treatment of postvasectomy infertility is microsurgical vasectomy reversal. This treatment also has the highest chance of resulting in delivery of a child for a single intervention.
An assumption exists that men with older female partners who seek treatment of post-vasectomy infertility should undergo in vitro fertilization (IVF) with intracytoplasmic sperm injection (ICSI) rather than vasectomy reversal. Although several studies have reviewed ICSI success rates with advancing maternal age, to our knowledge none has compared them to outcomes for vasectomy reversal in men with older partners.
The records of all patients with ovulating partners older than 37 years who underwent vasectomy reversal from 1994 through 1998 were reviewed. Patients were contacted to establish pregnancy and birth rates. Costs of vasectomy reversal, testicular sperm extraction, IVF and ICSI were obtained from the financial office of our institution.
A total of 29 patients underwent vasectomy reversal with a followup of 3 to 59 months (median 25). Median male age was 46 years (range 37 to 67) and median female age was 40 years (range 38 to 48). A total of 5 pregnancies and 4 live births were achieved. In the 23 patients followed for more than 1 year the pregnancy rate was 22% and live birth rate was 17%. Using this 17% birth rate at our 28,530. In comparison, using the 8% birth rate per cycle of ICSI for women older than 36 years at a cost of 103,940.
Vasectomy reversal appears to be cost-effective to achieve fertility in men with ovulating partners older than 37 years.
The Practice Guidelines Committee of the American Urological Association, Inc. (AUA) commissioned a Male Infertility Best Practice Policy Committee (MIBPPC) in 1998 to bridge the gap in male infertility between leading edge science and clinical practice, and provide urologists, gynecologists, reproductive endocrinologists, primary care practitioners, reproductive researchers and other health care providers with guidance for excellence of care in this rapidly changing field. The MIBPPC chose not to create a comprehensive treatise on male infertility, but rather to focus on areas that are new, poorly understood, poorly standardized, controversial and/or rapidly changing. The MIBPPC divided its efforts into 4 interrelated sections: 1) optimal evaluation of the infertile male, 2) evaluation of the azoospermic male, 3) management of obstructive azoospermia, and 4) varicocele and infertility. A separate report was created for each topic. The reports were submitted to peer review by 125 physicians and researchers from the disciplines of urology, gynecology, reproductive endocrinology, primary care and family medicine, andrology and reproductive laboratory medicine. The reports were then reviewed and approved by the Practice Guidelines Committee of the AUA the Practice Committee of the American Society for Reproductive Medicine (ASRM) and the boards of the 2 organizations. The reports were printed and distributed jointly by the AUA and ASRM in 2001. We reviewed each report of the MIBPPC.
Economic factors play a major role in the consideration of treatment options for male reproduction. This article has summarized the data and provided new insight into how patients, insurers, and populations evaluate competing therapies for male infertility. Many studies are difficult to interpret because of differing success rates and monetary bias. Future studies comparing line-by-line costs and reimbursements by independent sources may be the best way to evaluate different treatments.
The science of statistics forms the basis of much of what urologists do and why. Understanding basic statistics is crucial to the appropriate interpretation of urologic studies. As valid as they are, the statistics taught in medical school represent only a small part of what computation can do for the urologist. Contemporary tools such as neural computation coupled with electronic technology that provides increasingly greater computational power in smaller space hold promise to integrate into the field of clinical urology as seamlessly as a ballpoint pen or cystoscope.
We review the outcomes after vasectomy reversal for couples with female partners 35 years old or older.
A retrospective review of experience at 2 institutions was performed. Patency was defined as the presence of motile sperm. Patients with less than 6 months of followup were excluded from the patency rate analysis unless they had sperm in the semen. Similarly, patients with less than 12 months of followup or no ongoing interest in establishing conception were excluded from the pregnancy rate analysis unless they had established a pregnancy or they were azoospermic with sufficient followup.
A total of 46 men with partners 35 years old or older underwent vasectomy reversal at 2 institutions. Mean partner age was 37 +/- 2 years, and median obstructive interval was 10 years. Bilateral vasovasostomy was performed in 43 men, unilateral vasovasostomy in 2 and vasovasostomy/vasoepididymostomy in 1. Of the 46 men 27 had followup semen analyses with a patency rate of 81% (22). Transient patency occurred in 2 cases (7%). Pregnancy occurred in 35% of the couples (14 of 40 patients) with sufficient followup. The ongoing/live delivery rate was 33% (13 of 40 cases). The pregnancy and ongoing/delivery rates were 46% (12 of 26 patients) and 46% (12 of 26) for female partners 35 to 39 years old, and 14% (2 of 14) and 7% (1 of 14) for female partners older than 40, respectively.
Vasectomy reversal offers reasonable chance for success when the female partner is 35 years old or older. The chance for success is similar to that of a single cycle of in vitro fertilization with intracytoplasmic sperm injection. These couples should not be eliminated from consideration for reversal simply because the female partner is 35 years old or older.
Some urologists who perform vasectomy reversals are not experienced with performing VE. A model to preoperatively identify patients who may require referral to an experienced VE surgeon was created (). We tested the model at multiple institutions.
The model had previously been designed in 483 patients who underwent vasectomy reversal at 1 institution (100% sensitive and 59% specific for predicting the need for VE). It was based on time since vasectomy and patient age. We tested it prospectively in 33 patients and retrospectively in a total of 312 at 6 other institutions. The predictive accuracy of the model was compared to using a simple duration from vasectomy cutoff alone, as is used in clinical practice.
The model had 84% sensitivity and 58% specificity for detecting the need for VE in a total of 345 patients at 7 institutions. If using only a duration from vasectomy cutoff of 10 years to predict the need for VE, sensitivity was only 69%. At a cutoff of 4 years sensitivity was 99% but specificity was only 23%. Thus, the model performed better than any specific duration cutoff alone.
The predictive model provides 84% sensitivity for detecting patients who may require VE during vasectomy reversal across 7 institutions (58% specificity). The model more accurately predicts the need for VE than using a specific duration from vasectomy cutoff alone.
The most widely used reference values for human semen and sperm variables were developed by the World Health Organization (WHO) to help assess the fertility status of men interested in reproduction (typically a younger population). In this retrospective analysis, data from a large population of men aged 45 years or older were analyzed to derive semen and sperm reference ranges for an older population. Baseline semen samples were obtained from 1174 men with no or mild erectile dysfunction (ED) during the screening phase of two clinical trials evaluating the effects of a drug on human spermatogenesis. The median values and 95% reference ranges for 4 measured semen and sperm parameters (semen volume, sperm concentration, sperm motility, and sperm morphology) and 1 derived parameter (total sperm count) were calculated for the population and by age quartile. These references ranges were compared to established WHO reference values. Associations between the semen and sperm parameters and smoking status, alcohol use, and serum hormone concentrations were also analyzed. The mean age was 52.9 years (range: 45-80). Median semen volume, sperm motility, and sperm morphology parameters declined significantly with age. Only 46% of study subjects had baseline values for semen and sperm parameters that met or surpassed all the WHO reference values. This is the first study to statistically derive semen reference ranges from a large population of men aged 45 years or older. The observation that less than half the men in this study met all 4 WHO reference values for measured semen and sperm parameters underscores the need for age-specific reference ranges.
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